Purpose: To quantify possible differences in sprint mechanical outputs in handball and basketball players according to playing standard and position. Methods: Sprint tests of 298 male players were analyzed. Theoretical maximal velocity (v 0), horizontal force (F 0), horizontal power (P max), force–velocity slope (S FV), ratio of force (RFmax), and index of force application technique (D RF) were calculated from anthropometric and spatiotemporal data using an inverse dynamic approach applied to the center-of-mass movement. Results: National-team handball players displayed clearly superior 10-m times (0.03, ±0.02 s), 40-m times (0.12, ±0.07 s), F 0 (0.1, ±0.2 N·kg−1), v 0 (0.3, ±0.2 m·s−1), and P max (0.9, ±0.5 W·kg−1) than corresponding top-division players. Wings differed from the other positions in terms of superior 10-m times (0.02, ±0.01 to 0.07, ±0.02 s), 40-m times (0.07, ±0.05 to 0.27, ±0.07 s), F 0 (0.2, ±0.1 to 0.4, ±0.2 N·kg−1), v 0 (0.1, ±0.1 to 0.5, ±0.1 m·s−1), P max (0.7, ±0.4 to 2.0, ±0.5 W·kg−1), and RFmax (0.6, ±0.4 to 1.3, ±0.4%). In basketball, guards differed from forwards in terms of superior 10-m times (0.03, ±0.02 s), 40-m times (0.10, ±0.08 s), v 0 (0.2, ±0.1 m·s−1), P max (0.6, ±0.6 W·kg−1), and RFmax (0.4, ±0.3%). The effect magnitudes of the substantial differences observed ranged from small to large. Conclusions: The present results provide an overall picture of the force–velocity profile continuum in sprinting handball and basketball players and serve as useful background information for practitioners when diagnosing individual players and prescribing training programs.
Thomas A. Haugen, Felix Breitschädel, and Stephen Seiler
Thomas A. Haugen, Felix Breitschädel, Håvard Wiig, and Stephen Seiler
Purpose: To quantify possible differences in countermovement jump height across sport disciplines and sex in national-team athletes. Methods: In this cross-sectional study, 588 women (23  y, 66  kg) and 989 men (23  y, 82  kg) from 44 different sport disciplines (including 299 medalists from European Championships, World Championships, and/or Olympic Games) tested a countermovement jump on a force platform at the Norwegian Olympic Training Center between 1995 and 2018. Results: Athletic sprinting showed the highest values among the men (62.7 [4.8] cm) and women (48.4 [6.0] cm), clearly ahead of the long jump/triple jump (mean difference ± 90% CL: 6.5 ± 5.0 and 4.3 ± 4.1; very likely and likely; moderate) and speed skating sprint (11.4 ± 3.1 and 7.5 ± 5.5 cm; most likely and very likely; very large and moderate). These horizontally oriented sports displayed superior results compared with more vertically oriented and powerful sports such as beach volleyball, weightlifting, and ski jumping, both in men (from 2.9 ± 4.7 to 15.6 ± 2.9 cm; small to very large; possibly to most likely) and women (5.9 ± 4.8 to 13.4 ± 3.4 cm; large to very large; very likely to most likely), while endurance sports and precision sports were at the other end of the scale. Overall, the men jumped 33% higher than the women (10.3, ±0.6 cm; most likely; large). Conclusions: This study provides practitioners and scientists with useful information regarding the variation in countermovement jump height among national-team athletes within and across sport disciplines.
Thomas Haugen, Will Hopkins, Felix Breitschädel, Gøran Paulsen, and Paul Solberg
Purpose: To determine if generic off-ice physical fitness tests can provide useful predictions of ice hockey players’ match performance. Methods: Approximately 40 to 60 defenders and 70 to 100 forwards from the Norwegian male upper ice hockey league were tested for strength (1-repetition maximum in squat and bench press), power (40-m sprint and countermovement jump), and endurance (hanging sit-ups, chins, and 3000-m run) annually at the end of every preseason period between 2008 and 2017. Measures of match performance were each player’s season mean counts per match of assists, points, goals, penalty minutes, and plus-minus score. Results: Overall, match performance measures displayed trivial to small correlations with the fitness tests. More specifically, points per game had at most small correlations with measures of strength (range, approximately −0.2 to 0.3), speed (approximately −0.2 to 0.3), and endurance (approximately −0.1 to 0.3). After adjustments for age that showed moderate to large correlations with player match performance, multiple-regression analyses of each test measure still provided some predictability among players of the same age. However, players selected for the national team had substantially better mean scores for most tests and match performance measures than those not selected, with a moderate to large difference for age, 1-repetition maximum squat, and 1-repetition maximum bench press. Conclusions: Fitness tests had only marginal utility for predicting match performance in Norwegian hockey players, but those selected into the national team had better general fitness.
Thomas A. Haugen, Paul A. Solberg, Carl Foster, Ricardo Morán-Navarro, Felix Breitschädel, and Will G. Hopkins
The aim of this study was to quantify peak age and improvements over the preceding years to peak age in elite athletic contestants according to athlete performance level, sex, and discipline. Individual season bests for world-ranked top 100 athletes from 2002 to 2016 (14,937 athletes and 57,049 individual results) were downloaded from the International Association of Athletics Federations’ website. Individual performance trends were generated by fitting a quadratic curve separately to each athlete’s performance and age data using a linear modeling procedure. Mean peak age was typically 25–27 y, but somewhat higher for marathon and male throwers (∼28–29 y). Women reached greater peak age than men in the hurdles and middle- and long-distance running events (mean difference, ±90% CL: 0.6, ±0.3 to 1.9, ±0.3 y: small to moderate). Male throwers had greater peak age than corresponding women (1.3, ±0.3 y: small). Throwers displayed the greatest performance improvements over the 5 y prior to peak age (mean [SD]: 7.0% [2.9%]), clearly ahead of jumpers, long-distance runners, hurdlers, middle-distance runners, and sprinters (3.4, ±0.2% to 5.2, ±0.2%; moderate to large). Similarly, top 10 athletes showed greater improvements than top 11–100 athletes in all events (1.0, ±0.9% to 1.8, ±1.1%; small) except throws. Women improved more than men in all events (0.4, ±0.2% to 2.9, ±0.4%) except sprints. This study provides novel insight on performance development in athletic contestants that are useful for practitioners when setting goals and evaluating strategies for achieving success.